Bibliographic record
Abstract
What forms of knowledge and nonknowledge continue to haunt contemporary debates, and in what ways were they ‘known too well’ in the aftermath of 1968 to precipitate the falling out of favor of Marx and Marxism and the recasting of Macherey along with the rest of Althusser's circle as ‘structuralist dinosaurs’? And what might we learn from the staging of this encounter between Hegel and Spinoza, both in terms of the specific points of application and the method of enquiry? Macherey offers an answer to these questions not only in Hegel or Spinoza but also in a series of papers addressing Hegel's prior uptake in France—an engagement that had solidified tendencies in Hegel that were also, not coincidentally, the points of Hegel's misreading of Spinoza. Read together, they offer us a fuller picture of the long shadow—cast initially in Hegel's misinterpretation of Spinoza and amplified subsequently in the uptake of Hegel in France. To return explicitly to Hegel in 1979—even if to ‘surpass’ him—was in part to exhume a corpse, to demonstrate the ways that Hegel continued to haunt philosophy. Hegel or Spinoza was a response to the long and still active legacy of what we might call (borrowing from Macherey) Hegel à la Française.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.025 | 0.098 |
| Scholarly communication | 0.023 | 0.029 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.007 | 0.010 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".